Workshops Currently Available

The catalog below has information about upcoming workshops and online learning resources for Bioinformatics, Computational Biology, Statistics and Data Management Skills that are available from CCB and across HMS. The catalog includes learning objectives, intended target audience, pre-requisites and registration instructions. All workshops below are intended for HMS graduate students, postdocs, research staff and faculty.


 R Programming Workshops

Course Title
Host
Objectives
Target Audience
Pre-requisites
Duration
Schedule
Registration
Introduction to R HSPH Bioinformatics Core Learn the basics of R for reproducible data wrangling and visualizations (ggplot2).

Researchers needing basic knowledge of R to perform data analysis.

N/A Four, 2 hour sessions and self learning between sessions.

Tue, Jan 25, 2022,

Fri, Jan 28, 2022,

Tue, Feb 1, 2022,

Fri, Feb 4, 2022,

10am – 12pm

Registration Closed.
Introduction to R HSPH Bioinformatics Core Learn the basics of R for reproducible data wrangling and visualizations (ggplot2). Researchers needing basic knowledge of R to perform data analysis. N/A Four, 2 hour sessions and self learning between sessions.

Tue, Apr 19, 2022,

Fri, Apr 22, 2022,

Tue, Apr 26, 2022,

Fri, Apr 29, 2022

Registration will open 3 weeks prior to course start.

Introduction to R Online Resource

Harvard Catalyst

Provide both basic R programming knowledge and information on utilizing R to increase efficiency in data analysis.

Researchers needing basic R skills for data analysis, but prefer self-paced learning.

N/A

Learn at your own pace

Available through 12/30/2022

Register here!


Sequence Analysis Workshops

Course Title
Host
Objectives
Target Audience
Pre-requisites
Duration
Schedule
Registration
Introduction to Single Cell RNA-Seq Data Analysis HSPH Bioinformatics Core Designing a single-cell RNA-seq experiment, and efficiently managing and analyzing the data starting from count matrices.

Researchers needing to design and analyze a single cell RNA-Seq experiment using the Seurat package in R.

Introduction to R

Three, 2.5 hour sessions and self learning between sessions.

Fri, Feb 11, 2022,

Tue, Feb 15, 2022,

Fri, Feb 18, 2022,

9:30am – 12pm

Register Here!
Introduction to Bulk RNA-Seq Data Analysis (Part I) HSPH Bioinformatics Core Designing a bulk RNA-seq experiment, and efficiently managing and analyzing the data using the command-line interface and high-performance computing. Researchers needing to design a bulk RNA-seq experiment; generate a gene expression matrix; compute and assess QC metrics; automate a workflow on the O2 cluster. Introduction to Shell Three, 2.5 hour sessions & self learning between sessions.

Tue, Mar 29, 2022,

Fri, Apr 1, 2022,

Tue, Apr 5, 2022,

9:30am - 12:00pm

Register Here!
Introduction to Bulk RNA-Seq Data Analysis (Part II) HSPH Bioinformatics Core Introduce statistical methods and considerations utilized to perform differential gene expression analysis on bulk RNA-seq data; Best practices for quality control, how to  use DESeq2; review tools for functional analysis of DE genes and how to extract some biological meaning from large gene lists. Researchers who need to perform differential expression analysis at the gene-level using R, statistical analysis for assessing count data and visualize expression patterns. Introduction to R Four, 2 hour sessions & self learning between sessions.

Fri, May 6, 2022,

Tue, May 10, 2022,

Fri, May 13, 2022,

Tue, May 17, 2022,

10am - 12pm

Register Here!
Introduction to ChIP-Seq Analysis (Part I) HSPH Bioinformatics Core How to efficiently manage and analyze ChIP-seq data starting from sequence reads through to peak calling, using tools and software available on the HMS-RC's high performance compute cluster. Researchers needing to design and analysis ChIP-seq experiments.

Introduction to command-line interface workshop

Three, 2.5 hr sessions & self learning between sessions.

Fri, Jul 1, 2022,

Tue, Jul 5, 2022,

Fri, Jul 8, 2022,

9:30am - 12pm

Registration will open 3 weeks prior to course start.